Search and Filter Bubbles
Filter and search bubbles have been critical attributes for online marketers through advertising and play a huge role in personal online browsing. “Search” is a big part of Internet surfing. Users can endless amounts of answers from searching using search engines. Filter bubbles, on the other hand are the result of users searching in which the websites selectively display information that would go along with users’ opinion. Search and filter bubbles can be helpful in terms of seeking out unknown answers to some specific questions. Many users seem to have been trapped in their search filter bubbles because filter bubbles eliminate the information that disagrees with user opinions. Search and filter bubbles will continue to be a huge part of Internet(The Semantic Web 3.0) searching and browsing as more significant algorithms are developed to be more effective. Users should break out of their filter bubbles in order to positively search and surf the web so they can be exposed to a larger variety of information, instead of limiting themselves to what they normally search for. What is Search? Searching can be defined as to look at, read, or examine some collection of information. With search engines, this pertains to looking up information on the internet Dictionary.com. (2016). Search. Retrieved April 5, 2016, from Dictionary.com website: http://www.dictionary.com/browse/search . Common search engines that are widely used today include Google, Yahoo, Bing, Ask Jeeves, Baidu as well as others. Search works and can theoretically be capable of picking up all sixty trillion individual pages on the internet. Creators of search engines made it so users can search for a particular page or website based on the content that they have, as well as other factors Google. (n.d.). How Search Works. Retrieved April 5, 2016, from Google website: https://www.google.com/insidesearch/howsearchworks/thestory/ . The search engine keeps all of these pages information in something called "The Index", which contains over one-hundred million gigabytes of data. Search engines also contain algorithms that are implemented through a programming language . The text that the user searches for is than queried through the index for documents that are relevant to the thing the user searched. Google, for example, then uses two hundred factors to list the documents on the page in a particular order. New algorithms are being developed everyday to make search engines more effective at finding information/pages that users desire. Google tries to prevent spam from appearing on their search results. If they detect that certain documents (HTML pages) contain spam messages, those pages will be removed. There is a protocol that Google uses when detecting spam, which often includes contacting the site owner to see if they will change the spam content themselves. Searching in the modern web involves giving out information that companies will pay for from Google. The data and what users idea of privacy will be challenged in years to come, since this information is stored on data servers. Timeline and History of Search Engines The first concept of developing a database that could be searched by users was developed by Vannevar Bush in 1945, who wanted a repository of information that could be used for the benefit of mankind Wall, A. (2015). History of Search Engines: From 1945 to Google Today. Retrieved April 5, 2016, from SearchEngineHistory website: http://www.searchenginehistory.com/ . Gerard Salton was responsible for developing one of the first SMART searching technologies, that was the starting point for most search engines today . Ted Nelson was also a monumental figure who shaped how modern search engines are developed. He launched project Xanadu which was a precursor to the modern day internet. The circumstances regarding Project Xanadu's failure are still not agreed upon to this day . The first search engine ever developed is called Archie, which was developed by Alan Emtage in 1990, who was a student at McGill University in Montreal . The original intent of the name was supposed to be "archives", but it was shortened to Archie. University of Nevada System Computing Services group developed Veronica, which was in response to Archie. Instead though, Veronica was able to search plain text documents . Look at the semantic web's conception and it is seen how searching has been come more efficient Tips for More Efficient Searching Using search engines effectively saves time, and there are multiple ways you can efficiently search HINDY, J. (n.d.). 20 Tips To Use Google Search Efficiently. Retrieved April 5, 2016, from Lifehack.org website: http://www.lifehack.org/articles/technology/ 20-tips-use-google-search-efficiently.html . One technique is to use the tabs if you are searching for something specific, for example, if you are looking for an image, select "images" from the list of search options you have . You can also add quotes and hyphens to make your search more specific . Colons also allow you to search for specific sites (e.g. site: Facebook.com) . You can also find a link that links to another specific website (e.g. link:nhl.com ) . Adding astericks to your search allow a placeholder to be created that the search engine will fill in for you, so if you're looking for "got milk", you could search Got * . You can also find sites that are similar to other sites, and use google to search math questions, as well as search for a range of numbers . It's usually a good idea to keep search relatively simple and to gradually integrate new search terms . Also, spelling doesn't matter as much as it used to since Google's algorithms are really good at correcting words . You can also do money conversion and can find a specific file on Googles index . Category:Search Category:Filterbubbles Category:EliPariser Category:Ted What is Filter Bubble? A filter bubble is a result of a personalized search in which the websites selectively guesses information a user would like to see based on the user's past activities and information on the web, for example, locations, past search history, past browsed websites, etc. As a result of filter bubbles, users usualy only see information that agrees with their own viewpoints. Two of the major and commonly seen example of filter bubbles are Google's Personalized Search, and Facebook's personalized news stream. Google's personalized search is closely associated with a browser cookie record -- not only it searches all the web pages to the search term, but also websites that the user visited for their previous search results. Facebook's personalized news stream acts in a similar way. It pushes and services contents that is, aligned with users' own ideology and greately replied on what users are choosing ant the content that are clicking. The Facebook News Feed caused some complaints among Facebook users, because it is considered too easy for users to track (how Data Privacy and Tracking works?) activities like changes in relationship status, events, and conversation with other users. Background of Filter Bubbles The term, filter bubbles, was coined by Eli Pariser in his book by the same name. In 2011, Pariser presented his Ted Talk "Beware online 'filter bubbles'", warning people that there is a negative outcome to being trapped in "filter bubbles", which is what almost every web companies use to tailor their services according to our personal tastes and experiences. He suggests that the "filter bubbles" are stopping users from being exposed to information that is opposite to their own opinions, thus narrowing down their worldview. Pariser referred to the concept of filter bubbles in many other terms such as "personal ecosystem of information that's been catered by ...algorithms", "ideological frames", "figurative sphere surrounding you as you search the Internet", etc. He criticized Google and Facebook for having invisible algorithms that may block our exposure to new, opposing information, limits our capability to adapt to unfamiliar conditions. Pariser gave out a specific example in which one of the users searched Google for "BP" and got investment news about British Petroleum, while another user who searched the same thing got a result of Deepwater Horizon oil spill. These contents were shown to be "strikingly different". How to Pop the Filter Bubbles? The "filter bubble" has become a term for anxiety that the extremely personalized interfaces on the web will end up telling individuals and the society what they want to be exposed to, hiding anything opposing but significant. If you are not familiar with what exactly filter bubbles do to audiences, you should definitely start here by looking at Eli Pariser's argument in his TED talk about filter bubblesFilter bubble. (n.d.). Retrieved April 09, 2016, from https://en.wikipedia.org/wiki/Filter_bubble. 'A world constructed from the familiar is a world in which there’s nothing to learn … (since there is) invisible autopropaganda, indoctrinating us with our own ideas. -- Eli Pariser'Beware online "filter bubbles" (n.d.). Retrieved April 09, 2016, from http://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles Getting out of the filter bubbles and getting rid of metadata can be hard, but here are some new ways to try out: Clean up your browser often You can start by deleting cookies, clearing browser history, and etc. Since most search engines come up with results based on your previous link clicks, cleaning up your browser often might expose you to more information you should see. Use an alternative Search Engine There exists a search engine, called DuckDuckGo, that distinguishes itself from other search engines by not profiling its users and by showing all users the same search results for a given search term. By using DuckDuckGo as your search engine, you can protect your privacy and avoid personalized search results easier. Stop speculating and start looking Analyist showed that, our friends, both on social media or in personal life, are more likely to agree with our political attitudes than random strangers(also see Anonymity and Avatars) — 17 percent more likely to be exact. But it also showed that we tend to imagine our friends to be much more like us than they really are, thus inflating our perception of a filter bubble. People also tend to construct self-reinforcing filter bubbles because they already have distinct beliefs or ideologies. It is suggested that we should pay and raise more attention to things around us -- start looking and investigating ourselves. The more we know and the more we understand how tools like filter bubble exactly works, the less likely that we will be trapped in filter bubbles and the more likely we will be able to get the truth out of these limitationsGross, D. (2011). What the Internet is hiding from you. Retrieved April 09, 2016, from http://www.cnn.com/2011/TECH/web/05/19/online.privacy.pariser/. Related Topics The Semantic Web 3.0 Data Privacy and Tracking Anonymity and Avatars References Beware online "filter bubbles" (n.d.). Retrieved April 09, 2016, from http://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles Filter bubble. (n.d.). Retrieved April 09, 2016, from https://en.wikipedia.org/wiki/Filter_bubble Gross, D. (2011). What the Internet is hiding from you. Retrieved April 09, 2016, from http://www.cnn.com/2011/TECH/web/05/19/online.privacy.pariser/ HINDY, J. (n.d.). 20 Tips To Use Google Search Efficiently. Retrieved April 5, 2016, from Lifehack.org website: http://www.lifehack.org/articles/technology/20-tips-use-google-search-efficiently.html Wall, A. (2015). History of Search Engines: From 1945 to Google Today. Retrieved April 5, 2016, from SearchEngineHistory website: http://www.searchenginehistory.com Category:Search Category:Filterbubbles Category:EliPariser Category:Ted